In recent years, in the diagnosis of illness, “pathological diagnosis” using microscopic observation of tissue preparation of a lesioned part occupies a significant position. In the pathological diagnosis, the process from specimen preparation to diagnosis requires a lot of manpower, and automation is difficult. In particular, ability and experiment of a pathologist are important in diagnosis, and the diagnosis depends on personal ability of the pathologist. Meanwhile, the number of cancer patients increases due to population aging, and the number of pathologists is not sufficient at a medical site. From above, needs for image processing technology or remote diagnosis which supports the pathological diagnosis is increasing. In this manner, in order to classify a pathological tissue for supporting the pathological diagnosis, for example, there is a technology suggested in PTL 1. In PTL 1, low-magnification images are generated from high-magnification images, images are simply classified by the low-magnification images, and then, pathological tissues are classified by using the high-magnification images which are a base of the low-magnification images.